Structural Aspects Research Articles

Temporal-aware structure-semantic-coupled graph network for traffic forecasting

The spatial–temporal graph neural networks have been a critical approach to capturing the complicated spatial–temporal dependencies inherent in traffic series for more accurate forecasting. However, the issue of graph indistinguishability demands further attention, as graphs learned by existing methods tend to converge to implicit and indistinguishable representations, deviating from the genuine distribution. This issue can be attributed to the lack of three primary factors within graphs: the intrinsic graph features, the temporal-distinct features, and the node-distinct features. Aiming to address this problem, we propose a Temporal-Aware Structure-Semantic-Coupled Graph Network (TASSGN) in this paper. Firstly, we design a novel graph learning block to simultaneously learn the structural and semantic aspects of graphs, thereby capturing inherent graph features. Secondly, we propose an innovative Self-Sampling method to sample the relevant history series and present a Temporal-Aware Graphs Encoder to explicitly incorporate temporal information into graph learning and capture temporal-distinct features. Thirdly, sparse graphs are intentionally generated to capture node-distinct features. By combining these three key components together, our method is capable of overcoming the problem of graph indistinguishability and achieving state-of-the-art performances in traffic forecasting.

Structural features of a society in a state of exception: K. Marx, C. Schmitt, G. Agamben

The article focuses on the structural aspect of society in a state of exception, on its interpretation by K. Marx, С. Schmitt and G. Agamben. The goal was to reconstruct the understanding and conceptual description of extraordinariness in their direct statements about the structural elements of this state in their publications. Of course, such fragments are few, so the main difficulty was to read out intuitions from the texts that allow them to extend beyond the sphere that is the defining subject of these authors’ analysis. The final result is a certain list of terms and concepts, a kind of thesaurus of structural features of a society in a state of exclusivity. All of these authorities in various fields of knowledge recognize events, such as revolutions, wars, and epidemics, as an inevitable impulse that modifies the state of society. Something that upsets the circumstances of living together within nation-states is something like a devastating earthquake, which can be predicted but not prevented. It is something that abolishes the rules and regulations that are, or are only imagined to be, normal, actualizing a mode of action called the politics of extraordinary. The authors named above look at and try to understand the organics and mechanics of extreme, unusual, exceptional cases, i. e. , states of exceptionality from different paradigmatic perspectives (extraordinary, extraordinary are synonymous with exception). The vocabulary of structural features, which is distinguished from the works reviewed in this article, forms the core of the concept, which can be the methodological basis for studying the state of exceptionality in Ukraine, which is a consequence of the Russian aggression of February 24, 2022.

Pyrazolo - Pyrimidines as Targeted Anticancer Scaffolds - A Comprehensive Review.

Globally, cancer is the leading cause of death, which causes 10 million deaths yearly. Clinically, several drugs are used in treatment but due to drug resistance and multidrug resistance, there occurs a failure in the cancer treatment. The present review article is a comprehensive review of pyrazole and pyrimidine hybrids as potential anticancer agents. The review comprises more than 60 research works done in this field. The efficiency of the reported pyrazolopyrimidine fused heterocyclic with their biological data and the influence of the structural aspects of the molecule have been discussed. This review highlighted pyrazolo-pyrimidines as targeted anticancer agents with effect on multiple targets. The review will be helpful for the researchers involved in targeted drugs for cancer therapy for designing new scaffolds with pyrazolo-pyrimidine moieties.

Zur Entwicklung der Interpunktion in der Luther-Bibel

Abstract This study examines the development of punctuation in the Luther Bible in the period between 1522 and 2017 based on a passage from the Gospel of Matthew in 82 editions. The analysis is quantitative, qualitative, and at the same time hermeneutical: by repeatedly recalling the original printings, the aim is to capture all the relevant factors for historical punctuation. Among other things, aspects of the general text structure and line breaks are taken into account. From a syntactic point of view, various special cases are discussed, such as punctuation in non-sentential prepositional groups and in infinitives to block misinterpretation, but also the lack of punctuation in ›incorporated‹ main clauses. Furthermore, it is shown how the modern syntax-based punctuation since the middle of the 19th century runs counter Luther’s listener-oriented sentence construction.

Phase Transitions and Dynamics in Mixed Three- and Low-Dimensional Lead Halide Perovskites.

Lead halide perovskites are extensively investigated as efficient solution-processable materials for photovoltaic applications. The greatest stability and performance of these compounds are achieved by mixing different ions at all three sites of the APbX3 structure. Despite the extensive use of mixed lead halide perovskites in photovoltaic devices, a detailed and systematic understanding of the mixing-induced effects on the structural and dynamic aspects of these materials is still lacking. The goal of this review is to summarize the current state of knowledge on mixing effects on the structural phase transitions, crystal symmetry, cation and lattice dynamics, and phase diagrams of three- and low-dimensional lead halide perovskites. This review analyzes different mixing recipes and ingredients providing a comprehensive picture of mixing effects and their relation to the attractive properties of these materials.

Biomass C-doped three-dimensional Bi2WO6 for enhanced visible-light-driven photodegradation of diclofenac and rhodamine B

Photocatalysis as a green and efficient pollutant degradation technology, displaying great potential in environmental purification. By one step hydrothermal method in this study, flower-like Bi2WO6 with a large specific surface area was obtained, and the preparation of biomass carbon modified Bi2WO6 with sorghum stalks was also proposed to construct a series (BWO/x%C). The composites were effectively characterized in terms of several aspects of structure and properties. With the dyes rhodamine B and diclofenac as typical organic pollutants, the photocatalytic activity of the proposed photocatalysts was evaluated. Under visible light irradiation, the removal of rhodamine B by BWO/4%C reached 97.27% within 50 min and that of diclofenac reached 96.19% within 120 min, which were significantly favorable to single-phase Bi2WO6. The superiority of this system BWO/4%C is mainly due to its large specific surface area (33.51 m2/g), which provides additional reaction sites for contaminants. The UV–Vis DRS findings indicated that the modified biomass C reduced the band gap of Bi2WO6 and improved the availability of Bi2WO6 to visible light, and the separation efficiency of the electron and hole pairs of Bi2WO6 was improved due to the strong electron transfer ability of biomass C. The analyzing results of free radical trapping experiments confirmed that h+ and •O2- are the main active substances involved in the photodegradation reaction. The results of five cycle experiments exhibited that the degradation rate of rhodamine B still reached higher than 90%, confirming the good stability of the prepared material. Finally, a feasible degradation mechanism was proposed for the degradation of rhodamine B and diclofenac. It offers new ideas for the development of composite nano-photocatalytic materials targeting difficult-to-degrade organic pollutants.

Comprehensive assessment of TECENTRIQ® and OPDIVO®: analyzing immunotherapy indications withdrawn in triple-negative breast cancer and hepatocellular carcinoma.

Atezolizumab (TECENTRIQ®) and nivolumab (OPDIVO®) are both immunotherapeutic indications targeting programmed cell death 1 ligand 1 (PD-L1) and programmed cell death 1 (PD-1), respectively. These inhibitors hold promise as therapies for triple-negative breast cancer (TNBC) and hepatocellular carcinoma (HCC) and have demonstrated encouraging results in reducing the progression and spread of tumors. However, due to their adverse effects and low response rates, the US Food and Drug Administration (FDA) has withdrawn the approval of atezolizumab in TNBC and nivolumab in HCC treatment. The withdrawals of atezolizumab and nivolumab have raised concerns regarding their effectiveness and the ability to predict treatment responses. Therefore, the current study aims to investigate the immunotherapy withdrawal of PD-1/PD-L1 inhibitors, specifically atezolizumab for TNBC and nivolumab for HCC. This study will examine both the structural and clinical aspects. This review provides detailed insights into the structure of the PD-1 receptor and its ligands, the interactions between PD-1 and PD-L1, and their interactions with the withdrawn antibodies (atezolizumab and nivolumab) as well as PD-1 and PD-L1 modifications. In addition, this review further assesses these antibodies in the context of TNBC and HCC. It seeks to elucidate the factors that contribute to diverse responses to PD-1/PD-L1 therapy in different types of cancer and propose approaches for predicting responses, mitigating the potential risks linked to therapy withdrawals, and optimizing patient outcomes. By better understanding the mechanisms underlying responses to PD-1/PD-L1 therapy and developing strategies to predict these responses, it is possible to create more efficient treatments for TNBC and HCC.

Playing well with others: lessons from theatre for the health professions about collaboration, creativity and community.

Despite collaboration among different professions being recognized as fundamentally important to contemporary and future healthcare practice, the concept is woefully undertheorized. This has implications for how health professions educators might best introduce students to interprofessional collaboration and support their transition into interprofessional, collaborative workplaces. To address this, we engage in a conceptual analysis of published collaborative, interprofessional practices and conceptual understandings in theatre, as a highly collaborative art form and industry, to advance thinking in the health professions, specifically to inform interprofessional education. Our analysis advances a conceptualization of collaboration that takes place within a work culture of creativity and community, that includes four modes of collaboration, or the ways theatre practitioners collaborate, by: (1) paying attention to and traversing roles and hierarchies; (2) engaging in reciprocal listening and challenging of others; (3) developing trust and communication, and; (4) navigating uncertainty, risk and failure. We conclude by inviting those working in the health professions to consider what might be gleaned from our conceptualization, where the embodied and human-centred aspects of working together are attended to alongside structural and organizational aspects.

Vete a freír cristales

Abstract The constructional idiom [IRSE/ANDAR(SE)[imperative] a CLAUSE[infinitive]] (e.g., Vete a freír espárragos, lit. ‘go to fry asparagus’; Iros a tomar viento, lit. ‘go to get wind’) is commonly used in Spanish to convey the speaker’s strong rejection, and is a hallmark of colloquial language. This makes it an excellent candidate for exploring the phenomenon of extravagance, both because of these characteristics and its structure, which includes an empty slot filled with a clause headed by an infinitive. This structural aspect contributes to variability, as its high token frequency also results in high type frequency. The corpus analysis (Sketch Engine) presented in this paper allows us to illustrate the relationship between creativity and intensification, as well as between innovation and convention. Besides, it underscores the gradual nature of creativity, culminating in extravagance, which speakers employ to gain salience and, in turn, amplify the expressiveness and emotional impact of their statements.

Ab Initio Investigation of the Structural, Elastic, Dynamic, Electronic, and Magnetic Properties of Cubic Perovskite CeCrO3.

We presented the results of various aspects related to structural, elastic, electronic, dynamic, and magnetic parameters of cubic perovskite CeCrO3 by means of the full-potential linearized augmented plane wave (FP-LAPW) approach. The calculation of the unit cell volume against the total energy curve confirms that CeCrO3 exhibits higher energetic stability in the ferromagnetic (FM) order. Calculated structural aspects at equilibrium demonstrate excellent similarity to present information, lending credibility to our results. Moreover, monocrystalline elastic constants have been analyzed numerically. These constants provide insights into several related properties, including elastic anisotropy, mechanical stability, and several polycrystalline elastic aspects. Furthermore, the phonon dispersion curves obtained from our calculations reveal the existence of soft modes, which suggests the potential metastability of CeCrO3. Through an analysis of the energy band dispersions, the half-metallic nature of this material is confirmed, such as Eg = 3.00 and 3.13 eV for the HM state within generalized gradient approximations Perdew-Burke-Ernzerhof (GGA-PBE) and Tran-Blaha modified Becke-Johnson (TB-mBJ) calculations, respectively, as well as the FM total magnetic moment of 4.000 μB. Partial density of states (PDOS) aided in identifying the electronic states that contribute to the energy bands. Finally, the computed total magnetic moment aligns fit the theoretical findings available in the literature.

Synergistic potential in spinel ferrite MFe2O4 (M = Co, Ni) nanoparticles-mediated graphene oxide: Structural aspects, photocatalytic, and kinetic studies

The existence of artificial dyes in water is a significant environmental concern, as it can lead to poor water quality. Photodegradation is becoming an increasingly popular method for treating water contaminated with dyes. In this study, the photodegradation of Reactive Red 66 and Reactive Red 120 dyes, as well as textile wastewater, was investigated under UV and visible light irradiation. To enhance the photoresponse of the MFe2O4 (M = Co, Ni) nanoparticles, modifications were made by incorporating graphene oxide. The MFe2O4 nanoparticles and MFe2O4/GO nanocomposite photocatalysts were subjected to several characterization techniques, including FT-IR, Raman spectroscopy, XRD, DRS, zeta potential, VSM, TGA, DSC, BET, SEM, and EDAX analysis. Experiments were conducted to optimize several key parameters involved in the photodegradation process, including pH, photocatalyst dosage, initial dye concentration, and irradiation time. The removal efficiency of Reactive Red 66 and Reactive Red 120 dyes using CoFe2O4 nanoparticles was found to be 86.97 and 82.63%, respectively. Also, the removal percentage of these dyes using CoFe2O4/GO nanocomposite photocatalyst was 95.57 and 90.9% for Reactive Red 66 and Reactive Red 120, respectively. Experiments found that NiFe2O4 nanoparticles removed 90.92% of Reactive Red 66 dye and 84.7% of Reactive Red 120 dye. The NiFe2O4/GO nanocomposite photocatalyst showed even higher removal efficiencies, degrading 97.96% of Reactive Red 66 and 93.44% of Reactive Red 120. After three days of exposure to visible light irradiation, the removal percentage of Reactive Red 66 using MFe2O4 and MFe2O4/GO nanocomposite was investigated.

The characterisation of dental enamel using transmission Kikuchi diffraction in the scanning electron microscope combined with dynamic template matching

The remarkable physical properties of dental enamel can be largely attributed to the structure of the hydroxyapatite (HAp) crystallites on the sub-micrometre scale. Characterising the HAp microstructure is challenging, due to the nanoscale of individual crystallites and practical challenges associated with HAp examination using electron microscopy techniques. Conventional methods for enamel characterisation include imaging using transmission electron microscopy (TEM) or specialised beamline techniques, such as polarisation-dependent imaging contrast (PIC). These provide useful information at the necessary spatial resolution but are not able to measure the full crystallographic orientation of the HAp crystallites. Here we demonstrate the effectiveness of enamel analyses using transmission Kikuchi diffraction (TKD) in the scanning electron microscope, coupled with newly-developed pattern matching methods. The pattern matching approach, using dynamic template matching coupled with subsequent orientation refinement, enables robust indexing of even poor-quality TKD patterns, resulting in significantly improved data quality compared to conventional diffraction pattern indexing methods. The potential of this method for the analysis of nanocrystalline enamel structures is demonstrated by the characterisation of a human enamel TEM sample and the subsequent comparison of the results to high resolution TEM imaging. The TKD – pattern matching approach measures the full HAp crystallographic orientation enabling a quantitative measurement of not just the c-axis orientations, but also the extent of any rotation of the crystal lattice about the c-axis, between and within grains. Results presented here show how this additional information highlights potentially significant aspects of the HAp crystallite structure, including intra-crystallite distortion and the presence of multiple high angle boundaries between adjacent crystallites with rotations about the c-axis. These and other observations enable a more rigorous understanding of the relationship between HAp structures and the physical properties of dental enamel.

A comparative study of advanced evolutionary algorithms for optimizing microgrid performance under dynamic pricing conditions

The integration of microgrids into the existing power system framework enhances the reliability and efficiency of the utility grid. This manuscript presents an innovative mathematical paradigm designed for the optimization of both the structural and operational aspects of a grid-connected microgrid, leveraging the principles of Demand-Side Management (DSM). The focus of this work lies in a comprehensive exploration of the implications brought about by the Renewable Generation-Based Dynamic Pricing Demand Response (RGDP-DR) mechanism, particularly in terms of its influence on the optimal microgrid configuration, considering perspectives from end-users and the utility entity. This inquiry is rooted in a holistic assessment that encompasses technical and economic performance benchmarks. The RGDP-induced DR framework adeptly addresses the needs of the consumer base, showcasing notable efficiency and economic feasibility. To address the intricate nonlinear optimization challenge at hand, we employ an evolutionary algorithm named the "Dandelion Algorithm" (DA). A rigorous comparative study is conducted to evaluate the efficacy of four optimization techniques, affirming the supremacy of the proposed DA. Within this discourse, the complexity of microgrid sizing is cast as a dual-objective optimization task. The twin objectives involve minimizing the aggregate annual outlay and reducing emissions. The results of this endeavor unequivocally endorse the superiority of the DA over its counterparts. The DA demonstrates exceptional proficiency in orchestrating the most cost-effective microgrid and consumer invoice, surpassing the performance of alternative optimization methodologies.

The anti-corrosion performance of chaya leaf extracts on pure Mg substrates in Ringer´s solution

The chaya (Cnidoscolus aconitifolius) is a green, leafy vegetable domesticated since ancient Mayan culture, offering an abundance of valuable metabolites. This study investigated how three different extracts from Chaya leaves inhibit the corrosion of pure magnesium in Ringer's solution. Various techniques, such as scanning electron microscopy with energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and X-ray diffraction were employed to analyze the chemical, morphological, and structural aspects of the products formed on the magnesium surface after a 14-day exposure. The in vitro corrosion behavior was studied through open-circuit potential measurements and electrochemical impedance spectroscopy during immersion tests in physiological Ringer's solution with each extract. Polarization curves were also obtained to determine jcorr and Ecorr. Different morphologies were observed on the surfaces of the substrates due to each extract’s polarity. However, the results showed that the three chaya extracts retard, to some extent, the corrosion process, reducing the pH (from 9 to 6) and jcorr (from 18.2 to 1.12 µAcm−2) in comparison to untreated samples. The ethyl acetate-derived extract exhibited the highest percentage of inhibition (92.9%) according to the impedance results. These extracts could be a promising alternative for developing potential temporary implants for the human body and diverse industrial applications.

Hyperspectral image classification based on convolutional neural network

Hyperspectral remote sensing is the acquisition of spatial and spectral data of objects by detecting the electromagnetic waves reflected from them using a hyperspectral sensor. It enables the evaluation and identification of material composition, morphology, structure, and other aspects. Currently, hyperspectral imaging is widely applied in fields such as agriculture, environmental monitoring, forestry, medicine, and geology. However, traditional hyperspectral image classification encounters the problem of high complexity and overfitting when dealing with small sample sizes, requiring the use of advanced convolutional neural network models to address this issue. This paper primarily employs literature analysis, review, and comparative analysis methods to summarize the main challenges encountered when using convolutional neural networks for hyperspectral image classification. It also selects popular models in recent years to introduce, namely 3D-CNN model, hyperspectral pyramidal ResNet model and HybridSN model. This article focuses on whether these three models can solve problems that traditional classification models cannot solve, and what room for improvement there is, which will provide a reference for future research.

Investigation of optoelectronic and thermoelectric properties of novel BaCd2X2 (X = P, As, Sb) Zintl-phase for energy harvesting applications

The quest for new Zintl phases with promising thermoelectric properties has gained significant momentum recognitions to the precision of computational predictions. Our study presents an in-depth investigation of fundamental characteristics like structural, optoelectronic, optical, and transport aspects of BaCd2X2 (X = P, As, Sb) Zintl compounds. The stability of all compounds is firmly established through their optimized negative (-ve) formation energies and phonon dispersion spectra. Our findings affirm their robust structural integrity. Notably, we observe a semiconductor nature in these compounds, with calculated bandgap values of 1.35 eV for BaCd2P2, 0.85 eV for BaCd2As2, and 0.23 eV for BaCd2Sb2. Probing into optical properties, we uncover their potential utility in optoelectronic devices, as indicated by the optical response of these phases. We employ semi-classical Boltzmann theory, executed via BoltzTraP code, to explore their thermal behavior. Impressively higher values of Seebeck are attained, both at RT and elevated temperatures. Furthermore, the power factor exhibits an increasing trend with increasing temperature. Crucially, the analysis of the figure of merit (ZT) reveals promising values, 0.90, 0.81, and 0.72 for BaCd2X2 (X = P, As, Sb) at 300 K, respectively. These favorable optical and thermoelectric characteristics position these phases as attractive candidates for applications in optoelectronics and thermoelectric systems.

Large Language Models, Agency, and Why Speech Acts are Beyond Them (For Now) – A Kantian-Cum-Pragmatist Case

This article sets in with the question whether current or foreseeable transformer-based large language models (LLMs), such as the ones powering OpenAI’s ChatGPT, could be language users in a way comparable to humans. It answers the question negatively, presenting the following argument. Apart from niche uses, to use language means to act. But LLMs are unable to act because they lack intentions. This, in turn, is because they are the wrong kind of being: agents with intentions need to be autonomous organisms while LLMs are heteronomous mechanisms. To conclude, the article argues, based on structural aspects of transformer-based LLMs, that these LLMs have taken a first step away from mechanistic artificiality to autonomous self-constitution, which means that these models are (slowly) moving into a direction that someday might result in non-human, but equally non-artificial agents, thus subverting the time-honored Kantian distinction between organism and mechanism.

“DompeKeys”: a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases

The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecular fingerprints represent a widely employed class of descriptors; however, their generation process is time-consuming for large databases and is susceptible to bias. Therefore, descriptors able to accurately detect predefined structural fragments and devoid of lengthy generation procedures would be highly desirable. To meet additional needs, such descriptors should also be interpretable by medicinal chemists, and suitable for indexing databases with trillions of compounds. To this end, we developed—as integral part of EXSCALATE, Dompé’s end-to-end drug discovery platform—the DompeKeys (DK), a new substructure-based descriptor set, which encodes the chemical features that characterize compounds of pharmaceutical interest. DK represent an exhaustive collection of curated SMARTS strings, defining chemical features at different levels of complexity, from specific functional groups and structural patterns to simpler pharmacophoric points, corresponding to a network of hierarchically interconnected substructures. Because of their extended and hierarchical structure, DK can be used, with good performance, in different kinds of applications. In particular, we demonstrate how they are very well suited for effective mapping of chemical space, as well as substructure search and virtual screening. Notably, the incorporation of DK yields highly performing machine learning models for the prediction of both compounds’ activity and metabolic reaction occurrence. The protocol to generate the DK is freely available at https://dompekeys.exscalate.eu and is fully integrated with the Molecular Anatomy protocol for the generation and analysis of hierarchically interconnected molecular scaffolds and frameworks, thus providing a comprehensive and flexible tool for drug design applications.

Revisited and innovative perspectives of oral ulcer: from biological specificity to local treatment.

Mouth ulcers, a highly prevalent ailment affecting the oral mucosa, leading to pain and discomfort, significantly impacting the patient's daily life. The development of innovative approaches for oral ulcer treatment is of great importance. Moreover, a deeper and more comprehensive understanding of mouth ulcers will facilitate the development of innovative therapeutic strategies. The oral environment possesses distinct traits as it serves as the gateway to the digestive and respiratory systems. The permeability of various epithelial layers can influence drug absorption. Moreover, oral mucosal injuries exhibit distinct healing patterns compared to cutaneous lesions, influenced by various inherent and extrinsic factors. Furthermore, the moist and dynamic oral environment, influenced by saliva and daily physiological functions like chewing and speaking, presents additional challenges in local therapy. Also, suitable mucosal adhesion materials are crucial to alleviate pain and promote healing process. To this end, the review comprehensively examines the anatomical and structural aspects of the oral cavity, elucidates the healing mechanisms of oral ulcers, explores the factors contributing to scar-free healing in the oral mucosa, and investigates the application of mucosal adhesive materials as drug delivery systems. This endeavor seeks to offer novel insights and perspectives for the treatment of oral ulcers.

Impact of Histone Lysine Methyltransferase SUV4-20H2 on Cancer Onset and Progression with Therapeutic Potential.

Histone lysine methyltransferase SUV4-20H2, a member of the suppressor of variegation 4-20 homolog (SUV4-20) family, has a critical impact on the regulation of chromatin structure and gene expression. This methyltransferase establishes the trimethylation of histone H4 lysine 20 (H4K20me3), a repressive histone mark that affects several cellular processes. Deregulated SUV4-20H2 activity has been associated with altered chromatin dynamics, leading to the misregulation of key genes involved in cell cycle control, apoptosis and DNA repair. Emerging research evidence indicates that SUV4-20H2 acts as a potential epigenetic modifier, contributing to the development and progression of several malignancies, including breast, colon and lung cancer, as well as renal, hepatocellular and pancreatic cancer. Understanding the molecular mechanisms that underlie SUV4-20H2-mediated effects on chromatin structure and gene expression may provide valuable insights into novel therapeutic strategies for targeting epigenetic alterations in cancer. Herein, we discuss structural and functional aspects of SUV4-20H2 in cancer onset, progression and prognosis, along with current targeting options.